Human Behavior Modeling in SIoT

EasyChair Preprint 13274

Abstract

Behavior Modeling in Social Internet of Things (SIoT) is a rapidly emerging research area that aims to understand and predict human behavior in the context of interconnected smart devices and social interactions. SIoT brings together the power of IoT technologies and social networks to create intelligent environments that adapt to human needs and preferences. This abstract provides an overview of the key aspects and significance of human behavior modeling in SIoT.

The understanding of human behavior in SIoT is crucial for designing personalized and context-aware applications and services. It involves comprehending the factors that influence human behavior in such environments and overcoming the challenges associated with modeling complex human interactions with IoT devices. This abstract highlights the various approaches to human behavior modeling in SIoT, including sensor-based approaches that utilize wearable and environmental sensors, social sensing approaches that exploit social media and online platforms, and machine learning and AI techniques for predictive modeling and pattern recognition.

Keyphrases: Social Internet of Things (SIoT), human behavior modeling, personalized services, resource management, user experiences

@booklet{EasyChair:13274,
  author    = {Edwin Frank},
  title     = {Human Behavior Modeling in SIoT},
  howpublished = {EasyChair Preprint 13274},
  year      = {EasyChair, 2024}}